Checkout my CONFERENCE POSTER turML Model Poster.pdf for more details.
Use deep learning to learn a turbulence model from high fedelity data. The model can reasonably predict other turbulent flows.
We combine OpenFOAM C++ code with deep neural network python code to build a deep learning turbulence model.
- Extract high fidelity turbulence flow information in OpenFOAM using c++ code.
- Preprocessing the dataset and training a mode using python code.
- Emmbeding the DNN weights to OpenFOAM using c++ code.
- Combine the deep learning turbulence model with OpenFOAM turbulent flow calculation.
The model makes reasonable predicitons and outperforms conventional turbulence model for coures-mash condition. Below is some features map obtained using our deep learning turbulence model:
Enjoy!